Successfully reported this slideshow.
Upcoming SlideShare
×

# Rによるやさしい統計学 第16章 : 因子分析

16,725 views

Published on

Published in: Technology
• Full Name
Comment goes here.

Are you sure you want to Yes No

Are you sure you want to  Yes  No
• Dating direct: ❶❶❶ http://bit.ly/2F4cEJi ❶❶❶

Are you sure you want to  Yes  No

### Rによるやさしい統計学 第16章 : 因子分析

1. 1. R 16 @holidayworking 2006 6 26 @holidayworking () R 16 2006 6 26 1 / 18
2. 2. 1 2 3 R @holidayworking () R 16 2006 6 26 2 / 18
3. 3. ) Twitter: @holidayworking : : : T-SQUARE F1 : Java, PL/SQL: Python, Ruby: @holidayworking () R 16 2006 6 26 3 / 18
4. 4. i i i i : 5 @holidayworking () R 16 2006 6 26 4 / 18
5. 5. R R factanal factanal(x, factors, rotation = "varimax") x factors rotation (varimax) (promax) @holidayworking () R 16 2006 6 26 5 / 18
6. 6. 5 1 60.00 64.00 55.00 55.00 55.00 2 41.00 44.00 46.00 55.00 44.00 3 55.00 63.00 62.00 58.00 70.00 4 60.00 45.00 44.00 53.00 49.00 5 58.00 56.00 61.00 67.00 58.00 ( ) 195 64.00 47.00 52.00 42.00 48.00 196 39.00 36.00 35.00 38.00 36.00 197 42.00 43.00 43.00 57.00 39.00 198 64.00 58.00 47.00 33.00 56.00 199 49.00 47.00 46.00 49.00 54.00 200 51.00 51.00 49.00 50.00 46.00 @holidayworking () R 16 2006 6 26 6 / 18
7. 7. > <- cor( ) > 1.0000000 0.5500166 0.1953799 0.1630274 0.4275140 0.5500166 1.0000000 0.3317530 0.2944938 0.5178159 0.1953799 0.3317530 1.0000000 0.5301135 0.4575891 0.1630274 0.2944938 0.5301135 1.0000000 0.3876493 0.4275140 0.5178159 0.4575891 0.3876493 1.0000000 0.55 0.53 4 0.39 0.52 ⇒ @holidayworking () R 16 2006 6 26 7 / 18
8. 8. 1 > eigen( ) \$values [1] 2.5573782 1.0656034 0.5058941 0.4461472 0.4249772 \$vectors [,1] [,2] [,3] [,4] [,5] [1,] -0.4040025 0.57915506 -0.3526733 -0.30988872 0.53004894 [2,] -0.4791362 0.36314955 -0.1046695 0.07323541 -0.78881668 [3,] -0.4380493 -0.48395278 0.2494573 -0.71311577 -0.05603054 [4,] -0.4064807 -0.54402387 -0.6062633 0.39786745 0.11383232 [5,] -0.5000967 0.05029462 0.6594556 0.48142803 0.28411115 @holidayworking () R 16 2006 6 26 8 / 18
9. 9. > <- factanal( , factors=2) > print( , cutoff=0) Call: factanal(x = , factors = 2) Uniquenesses Loadings Uniquenesses: SS loadings 0.471 0.395 0.379 0.548 0.491 Proportion Var Loadings: Cumulative Var Factor1 Factor2 0.722 0.084 0.730 0.268 0.177 0.768 0.156 0.654 0.537 0.470 Factor1 Factor2 SS loadings 1.399 1.317 Proportion Var 0.280 0.263 Cumulative Var 0.280 0.543 Test of the hypothesis that 2 factors are sufficient. The chi square statistic is 0.08 on 1 degree of freedom. @holidayworking () The p-value is 0.782 R 16 2006 6 26 9 / 18
10. 10. 1 > <- 1 - \$uniquenesses > 0.5288198 0.6049597 0.6213085 0.4523362 0.5087881 @holidayworking () R 16 2006 6 26 10 / 18
11. 11. 1 2 0.722 0.084 0.529 0.730 0.268 0.605 0.537 0.470 0.509 0.177 0.768 0.621 0.156 0.654 0.452 0.722 1.317 1 ⇒ 2 ⇒ @holidayworking () R 16 2006 6 26 11 / 18
12. 12. @holidayworking () R 16 2006 6 26 12 / 18
13. 13. > <- factanal( , factors=2,rotation="promax") > print( , cutoff=0) Call: factanal(x = , factors = 2, rotation = "promax") Uniquenesses: 0.471 0.395 0.379 0.548 0.491 Loadings: Factor1 Factor2 0.801 -0.156 0.749 0.050 -0.051 0.815 -0.038 0.692 0.461 0.348 Factor1 Factor2 SS loadings 1.419 1.291 Proportion Var 0.284 0.258 Cumulative Var 0.284 0.542 Test of the hypothesis that 2 factors are sufficient. The chi square statistic is 0.08 on 1 degree of freedom. @holidayworking () The p-value is 0.782 R 16 2006 6 26 13 / 18
14. 14. > <- factanal( , factors=2,rotation="none") > print( , cutoff=0) Call: factanal(x = , factors = 2, rotation = "none") Uniquenesses: 0.471 0.395 0.379 0.548 0.491 Loadings: Factor1 Factor2 0.583 -0.435 0.714 -0.307 0.657 0.436 0.563 0.368 0.713 -0.028 Factor1 Factor2 SS loadings 2.106 0.611 Proportion Var 0.421 0.122 Cumulative Var 0.421 0.543 Test of the hypothesis that 2 factors are sufficient. The chi square statistic is 0.08 on 1 degree of freedom. @holidayworking () The p-value is 0.782 R 16 2006 6 26 14 / 18
15. 15. > <- promax(loadings( ), m=4) > print( ) \$loadings Loadings: Factor1 Factor2 0.801 -0.156 0.749 0.815 0.692 0.461 0.348 Factor1 Factor2 SS loadings 1.419 1.291 Proportion Var 0.284 0.258 Cumulative Var 0.284 0.542 \$rotmat [,1] [,2] [1,] 0.6062459 0.5303245 [2,] -1.0284319 1.0695617 @holidayworking () R 16 2006 6 26 15 / 18
16. 16. rotmat > <- solve(t( \$rotmat)%*% \$rotmat) > [,1] [,2] [1,] 1.0000000 0.5462117 [2,] 0.5462117 1.0000000 1 2 0.5462117 @holidayworking () R 16 2006 6 26 16 / 18
17. 17. R factanal @holidayworking () R 16 2006 6 26 17 / 18
18. 18. @holidayworking () R 16 2006 6 26 18 / 18